Research Scientist, Soft Robotics (PhD University Grad)

(Redmond, WA)

Careers at Oculus

Part of Facebook

You're an engineer or roboticist with a deep knowledge in soft materials and a passion for working on breakthrough soft robotic technology. You are particularly interested in modeling and simulating highly deformable composites, tissues, and structures. At Oculus Research, you'll be involved in building cutting-edge prototypes and user experiences that explore the future of virtual reality (VR) and augmented reality (AR). Work alongside expert research scientists, mechanical engineers, material scientists, electrical engineers and software engineers to create the technology that makes VR and AR pervasive and universal. Join the adventure of a lifetime as we make science fiction real and change the world.

Responsibilities

  • Lead research into computational modeling and numerical simulation of soft structures and machines.
  • Collaborate on machine learning research towards the discovery of scientific models capable of predicting soft mechanism behavior.
  • Collaborate on research towards real-time and robust control strategies of soft robots exhibiting rate-dependent, hysteretic, and highly non-linear dynamics.
  • Work closely with other expert researchers on topics from additive manufacturing to human psychophysics to materials science.
  • Define fundamental challenges and long-term vision for your own research as well as for your collaborative teams.
  • Learn constantly, dive into new areas with unfamiliar technologies, and embrace the ambiguity of AR/VR problem solving.
  • Patent and publish high impact discoveries.
Minimum Qualifications
  • Currently has or is in the process of obtaining a PhD degree or completing a postdoctoral assignment in the field of robotics, mechanical engineering or bioengineering.
  • 3+ years experience with computational modeling and numerical simulation of soft matter, soft robots, or highly deformable structures.
  • Experience with soft materials research, including publications/patents.
  • Experience working across disciplines.
  • Must be available to start employment on or after May 1st 2018.
  • Interpersonal skills: cross-group and cross-culture collaboration
  • Able to obtain work authorization in the U.S. beginning in 2018.
Preferred Qualifications
  • Expertise in Abaqus, ANSYS, COMSOL, and/or custom FEA software.
  • Experience running fluid-structure interaction (FSI) simulations.
  • Basic experience implementing machine learning algorithms. (e.g. CNN, RNN, etc., using software like TensorFlow, Torch, etc.)
  • Basic experience implementing controllers in hardware, with strong preference towards soft and highly compliant structures. (e.g. PID, LQR, KF, EKF, UKF, etc.)
  • Experience leading and mentoring other researchers.
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